Invest Like the Best with Patrick O'Shaughnessy
· Patrick O'Shaughnessy, Shyam Sankar
[00:00:00] S0: Did you have your own gamma ray moment? Was there an original moment like that for you where you discovered your own potential? [00:00:00] S1: The article talks about the deployment at the COIC. I think that was a seminal one where I was leading the deployment, it was all on me. And it was never obvious until basically the last second whether it was going to work or not. And it allowed me to learn a lot of lessons along the way, which is really where I internalized, "Oh, success looks like a lot of pain." That instinct to figure out how to reduce the pain, like how do I do this the next time with less pain, is exactly the wrong instinct. [00:00:00] S0: If you were giving a commencement speech to a group of people that heard this conversation, how would you urge people to seek that out? Like if someone is pre-gamma exposure and they're interested in that test for themselves, how can people expose themselves to that test?
· Patrick O'Shaughnessy, Shyam Sankar
[00:00:00] S0: If you were giving a commencement speech to a group of people that heard this conversation, how would you urge people to seek that out? Like if someone is pre-gamma exposure and they're interested in that test for themselves, how can people expose themselves to that test? [00:00:00] S1: I think this is the conspiracy of the people around you who give you that chance. I don't know why Kevin Hartz hired me as some Stanford grad student coming to talk to him, but the fact that he took the bet and just threw me out there, that was the first time I got to jump off the deep end in many ways. So I really think, how can you find it? You're assessing the people who are hiring you as much as they're assessing you. Is this an environment that I think is going to bet on me or is this an environment that wants me to be a veal cow? Are they going to be able to tolerate my eccentricities or are they going to try to squash that? [00:00:00] S0: How do you know someone's worth betting on? The other side of that equation. New unproven talent, how do you know? [00:00:00] S1: At some point, it becomes lizard brain. You get enough reps in doing it, but early on, I think the early indicators would be first derivative, proof of some sort of sui generis. Did they create anything from zero to one? And then expression of agency and initiative. Here's the simplest way I'd say it. If I give this person an inch, can they turn it into a mile? And the worst sort of bet to make is I gave this person a mile and somehow they turned it into an inch.
· Shyam Sankar, Patrick O'Shaughnessy
[00:00:00] S1: At some point, it becomes lizard brain. You get enough reps in doing it, but early on, I think the early indicators would be first derivative, proof of some sort of sui generis. Did they create anything from zero to one? And then expression of agency and initiative. Here's the simplest way I'd say it. If I give this person an inch, can they turn it into a mile? And the worst sort of bet to make is I gave this person a mile and somehow they turned it into an inch. [00:00:00] S0: Yeah, it's an incredibly powerful idea and it seems like the culture of Palantir – I mean, obviously there's tons of founders that have come out of this that have mega agency or something like this. If you think about Palantir's future for the next 10 years, now 19 years in, what do you hope changes most in the next 10? Obviously, it's now a huge company, it's one of the bigger companies by market cap in the country and in the world, doing lots of really interesting work with lots of interesting customers. But generally speaking, what are your hopes for it over the next five to 10 years?
· Shyam Sankar, Patrick O'Shaughnessy
[00:00:00] S1: All value creation is downstream of the culture. Continuing to be an environment where a new person can come in and just have huge responsibility, be in charge of people who've been here 10 years or not. It's like that org structure, I call it a quantum org structure. I don't think a flat org structure is optimal. That doesn't actually work. I think what you want is an org structure that can crystallize, is the right structure to solve the problem as it exists today and is able to reform as the problem manipulates tomorrow. And you can see the pathology of big companies as they go through some sort of big reorg every five years, even if you just steel man it. Probably most of them are wrong, even at inception. But if you just steel man it and say, "Hey, they just reorged. This is the right org structure for this company today." Every day, the entropy is against them. And every day, it's slightly more wrong than it was before. If you're so ossified and committed to your structure that you have to wait until it's totally broken before you reorganize it again, that's a fundamental weakness. So that plasticity and how your commitment to working backwards from the problems, that is how we generate value. And that has to be consistent. And I think if we can protect that and promote that, promulgate that culture in the future generations, we're gonna keep winning. [00:00:00] S0: What critique of Palantir do you take the most seriously?
· Patrick O'Shaughnessy, Shyam Sankar
[00:00:00] S0: What critique of Palantir do you take the most seriously? [00:00:00] S1: When you have a structure like this, you don't get to spend nearly as much time with people as you'd want. The rate of irradiation is very heterogeneous. There's some sort of bimodal distribution for how long people stay at Palantir. The probability that you'll stay for a decade plus if you've stayed three years is incredibly high. But roughly around the three-year mark, everyone faces this crucible where they look around and they say, "This place is so fucked up and crazy." And they have to understand, oh, but that's the feature of it, and then they'll stay. [00:00:00] S0: Sign up for it or not, right. [00:00:00] S1: Or they'll say, this is the bug of it and I gotta get out of here and it's not gonna work. The critique I take most seriously, because I think with a little bit of help, a lot more people can make that hump. And that's the future of the business. It’s in those people. [00:00:00] S0: We have you to blame for how many freaking pitches we have to take that involve some forward deployed something or other in a company these days. You were the one that really pioneered the success of this model at Palantir. Everyone is saying it now, that every company has to have forward deployed engineers or forward deployed so-and-sos to be successful. Obviously, I think that's not true for every company. It's true in Palantir's case for sure. Can you tell us the story of what this term means, where it came from and why it's powerful?
· Shyam Sankar
[00:00:00] S1: We could start by maybe thinking about my critique of the conventional software industrial complex, which is that you're sitting, let's just say in Palo Alto and you're building this piece of software and your essential feedback loop on "Is this software valuable" is, "Can I sell it?" And if someone's willing to pay for it, it must be valuable. That's an okay feedback loop. There's a stronger feedback loop, which is "Is the software valuable? Did it deliver the outcome?" The only way you can assess that is actually in the field with the end user, on the factory floor, in the foxhole. So in our case, it wasn't gonna be enough. You have this weird division between the IT buyer and the operator. The validation is going to come from the operator. The idea was really almost to build software through backpropagation. Hey, how do you go to the person who has the problem? You're showing up with your best thesis of what you've built in the metaphorical Palo Alto, but then you are not just sending a sales engineer out there whose job is to try to ring up the sale. You're sending someone out there who is obsessed with whether it's going to generate an impact in the world or not, and is willing to continuously solve backward and is technical enough to understand the full stack. How would we take the specific and learn how to generalize it over time, in terms of the product? One way of thinking about this is, there really are two types of engineers. There are people who know how to build the right thing, and there are people who know how to build it the right way. And their dopamine hits come out of different things. The people who know how to build the right thing, they're more like MacGyver. Their high in life is, "I solved the problem." In their minds, solving the right problem is 80% of the work. On the other end, you have engineers who are more like artists in the traditional sense. "Don't you see how beautiful the thing I built is?" The architectural elegance, the scalability of it, that's what gives them the high. Nevermind that it doesn't solve a problem anyone cares about. It's art on its own. It should be appreciated. And I think about this like vector math. So the forward deployed engineers skew towards this hacker mentality. The product engineers skew towards this artist mentality.